Palm Print Recognition

Palm Print Recognition free pdf ebook was written by NSTC Subcommittee On Biometrics on March 31, 2006 consist of 10 page(s). The pdf file is provided by www.biometrics.gov and available on pdfpedia since May 20, 2011.

to be one of the most well-known and best publicized biometrics. www.biometrics.gov. subcommittee on biometrics. co-chair: duane blackburn (ostp) co-chair: ...

Palm Print RecognitionIntroductionPalm print recognition inherently implements many of the samematching characteristics that have allowed fingerprint recognitionto be one of the most well-known and best publicized biometrics.Both palm and finger biometrics are represented by theinformation presented in a friction ridge impression. Thisinformation combines ridge flow, ridge characteristics, and ridgestructure of the raised portion of the epidermis. The datarepresented by these friction ridge impressions allows adetermination that corresponding areas of friction ridgeimpressions either originated from the same source or could nothave been made by the same source. Because fingerprints andpalms have both uniqueness and permanence, they have beenused for over a century as a trusted form of identification.However, palm recognition has been slower in becomingautomated due to some restraints in computing capabilities andlive-scan technologies. This paper provides a brief overview ofthe historical progress of and future implications for palm printbiometric recognition.HistoryIn many instances throughout history, examination of handprintswas the only method of distinguishing one illiterate person fromanother since they could not write their own names. Accordingly,the hand impressions of those who could not record a name butcould press an inked hand onto the back of a contract became anacceptable form of identification. In 1858, Sir William Herschel,working for the Civil Service of India, recorded a handprint on theback of a contract for each worker to distinguish employees fromothers who might claim to be employees when payday arrived.This was the first recorded systematic capture of hand and fingerimages that were uniformly taken for identification purposes.1The first known AFIS system built to support palm prints isbelieved to have been built by a Hungarian company. In late1994, latent experts from the United States benchmarked thepalm system and invited the Hungarian company to the 1995International Association for Identification (IAI) conference. Thepalm and fingerprint identification technology embedded in thepalm system was subsequently bought by a US company in 1997.This Document Last Updated: 7 August 2006Page 1 of 10

You're reading the first 10 out of 10 pages of this docs, please download or login to readmore.

Palm Print RecognitionIn 2004, Connecticut, Rhode Island and California establishedstatewide palm print databases that allowed law enforcementagencies in each state to submit unidentified latent palm prints tobe searched against each other's database of known offenders.2,3Australia currently houses the largest repository of palm prints inthe world. The new Australian National Automated FingerprintIdentification System (NAFIS) includes 4.8 million palm prints.The new NAFIS complies with the ANSI/NIST international standardfor fingerprint data exchange, making it easy for Australian policeservices to provide fingerprint records to overseas police forcessuch as Interpol or the FBI, when necessary.4Over the past several years, most commercial companies thatprovide fingerprint capabilities have added the capability forstoring and searching palm print records. While several state andlocal agencies within the US have implemented palm systems, acentralized national palm system has yet to be developed.Currently, the Federal Bureau of Investigation (FBI) CriminalJustice Information Services (CJIS) Division houses the largestcollection of criminal history information in the world. Thisinformation primarily utilizes fingerprints as the biometricallowing identification services to federal, state, and local usersthrough the Integrated Automated Fingerprint IdentificationSystem (IAFIS). The Federal Government has allowed maturationtime for the standards relating to palm data and live-scan captureequipment prior to adding this capability to the current servicesoffered by the CJIS Division. The FBI Laboratory Division hasevaluated several different commercial palm AFIS systems to gaina better understanding of the capabilities of various vendors.Additionally, state and local law enforcement have deployedsystems to compare latent palm prints against their own palmprint databases. It is a goal to leverage those experiences andapply them towards the development of a National Palm PrintSearch System.In April 2002, a Staff Paper on palm print technology and IAFISpalm print capabilities was submitted to the IdentificationServices (IS) Subcommittee, CJIS Advisory Policy Board (APB). TheJoint Working Group then moved “for strong endorsement of theplanning, costing, and development of an integrated latent printcapability for palms at the CJIS Division of the FBI. This shouldproceed as an effort along the same parallel lines that IAFIS wasdeveloped and integrate this into the CJIS technicalcapabilities….”5This Document Last Updated: 7 August 2006Page 2 of 10

Palm Print RecognitionAs a result of this endorsement and other changing business needsfor law enforcement, the FBI announced the Next GenerationIAFIS (NGI) initiative. A major component of the NGI initiative isthe development of the requirements for and deployment of anintegrated National Palm Print Service. Law enforcementagencies indicate that at least 30 percent of the prints lifted fromcrime scenes — from knife hilts, gun grips, steering wheels, andwindow panes — are of palms, not fingers.6For this reason,capturing and scanning latent palm prints is becoming an area ofincreasing interest among the law enforcement community. TheNational Palm Print Service is being developed on the basis ofimproving law enforcement’s ability to exchange a more completeset of biometric information, making additional identifications,quickly aiding in solving crimes that formerly may have not beenpossible, and improving the overall accuracy of identificationthrough the IAFIS criminal history records.ApproachConceptPalm identification, just like fingerprint identification, is based onthe aggregate of information presented in a friction ridgeimpression. This information includes the flow of the frictionridges (Level 1 Detail), the presence or absence of features alongthe individual friction ridge paths and their sequences (Level 2Detail), and the intricate detail of a single ridge (Level 3 detail).To understand this recognition concept, one must first understandthe physiology of the ridges and valleys of a fingerprint or palm.When recorded, a fingerprint or palm print appears as a series ofdark lines and represents the high, peaking portion of the frictionridged skin while the valley between these ridges appears as awhite space and is the low, shallow portion of the friction ridgedskin. This is shown in Figure 1.Figure 1: Fingerprint Ridges (Dark Lines) vs. Fingerprint Valleys (White Lines).This Document Last Updated: 7 August 2006Page 3 of 10

Palm Print RecognitionPalm recognition technology exploits some of these palmfeatures. Friction ridges do not always flow continuouslythroughout a pattern and often result in specific characteristicssuch as ending ridges or dividing ridges and dots. A palmrecognition system is designed to interpret the flow of the overallridges to assign a classification and then extract the minutiaedetail — a subset of the total amount of information available, yetenough information to effectively search a large repository ofpalm prints. Minutiae are limited to the location, direction, andorientation of the ridge endings and bifurcations (splits) along aridge path. The images in Figure 2 present a pictorialrepresentation of the regions of the palm, two types of minutiae,and examples of other detailed characteristics used during theautomatic classification and minutiae extraction processes.IslandPoresRidgeEndingRidgeBifurcationFigure 2: Palm Print and Close-up Showing Two Typesof Minutiae and Other Characteristics.HardwareA variety of sensor types — capacitive, optical, ultrasound, andthermal — can be used for collecting the digital image of a palmsurface; however, traditional live-scan methodologies have beenslow to adapt to the larger capture areas required for digitizingpalm prints. Challenges for sensors attempting to attain high-resolution palm images are still being dealt with today. One ofthe most common approaches, which employs the capacitivesensor, determines each pixel value based on the capacitancemeasured, made possible because an area of air (valley) hassignificantly less capacitance than an area of palm (ridge). Otherpalm sensors capture images by employing high frequencyultrasound or optical devices that use prisms to detect the changeThis Document Last Updated: 7 August 2006Page 4 of 10

Palm Print Recognitionin light reflectance related to the palm. Thermal scannersrequire a swipe of a palm across a surface to measure thedifference in temperature over time to create a digital image.Capacitive, optical, and ultrasound sensors require onlyplacement of a palm.SoftwareSome palm recognition systems scan the entire palm, while othersrequire the palms to be segmented into smaller areas to optimizeperformance. Maximizing reliability within either a fingerprint orpalm print system can be greatly improved by searching smallerdata sets. While fingerprint systems often partition repositoriesbased upon finger number or pattern classification, palm systemspartition their repositories based upon the location of a frictionridge area. Latent examiners are very skilled in recognizing theportion of the hand from which a piece of evidence or latent lifthas been acquired. Searching only this region of a palmrepository rather than the entire database maximizes thereliability of a latent palm search.Like fingerprints, the three main categories of palm matchingtechniques are minutiae-based matching, correlation-basedmatching, and ridge-based matching. Minutiae-based matching,the most widely used technique, relies on the minutiae pointsdescribed above, specifically the location, direction, andorientation of each point. Correlation-based matching involvessimply lining up the palm images and subtracting them todetermine if the ridges in the two palm images correspond. Ridge-based matching uses ridge pattern landmark features such assweat pores, spatial attributes, and geometric characteristics ofthe ridges, and/or local texture analysis, all of which arealternates to minutiae characteristic extraction. This method is afaster method of matching and overcomes some of the difficultiesassociated with extracting minutiae from poor quality images.The advantages and disadvantages of each approach vary basedon the algorithm used and the sensor implemented. Minutiae-based matching typically attains higher recognition accuracy,although it performs poorly with low quality images and does nottake advantage of textural or visual features of the palm.Processing using minutiae-based techniques may also be timeconsuming because of the time associated with minutiaeextraction. Correlation-based matching is often quicker to processbut is less tolerant to elastic, rotational, and translationalvariances and noise within the image. Some ridge-based matchingcharacteristics are unstable or require a high-resolution sensor toThis Document Last Updated: 7 August 2006Page 5 of 10

Palm Print Recognitionobtain quality images. The distinctiveness of the ridge-basedcharacteristics is significantly lower than the minutiaecharacteristics.United States Government EvaluationsUnlike several other biometrics, a large-scale Government-sponsored evaluation has not been performed for palmrecognition. The amount of data currently available for testpurposes has hindered the ability for not only the FederalGovernment but also the vendors in efficiently testing andbenchmarking commercial palm systems. The FBI Laboratory iscurrently encoding its hard-copy palm records into three of themost popular commercial palm recognition systems. This activity,along with other parallel activities needed for establishing aNational Palm Print Service, will address these limitations andpotentially provide benchmark data for US Governmentevaluations of palm systems.Standards OverviewJust as with fingerprints, standards development is an essentialelement in palm recognition because of the vast variety ofalgorithms and sensors available on the market. Interoperability isa crucial aspect of product implementation, meaning that imagesobtained by one device must be capable of being interpreted by acomputer using another device. Major standards efforts for palmprints currently underway are the revision to the ANSI NIST ITL-2000 Type-15 record. Many, if not all, commercial palm AFISsystems comply with the ANSI NIST ITL-2000 Type-15 record forstoring palm print data. Several recommendations to enhance therecord type are currently being “vetted” through workshopsfacilitated by the National Institute for Standards and Technology.Specifically, enhancements to allow the proper encoding andstorage of Major Case Prints, essentially any and all friction ridgedata located on the hand, are being endorsed to support theNational Palm Print Service initiative of NGI.This Document Last Updated: 7 August 2006Page 6 of 10

Palm Print RecognitionSummaryEven though total error rates are decreasing when comparing livescan enrollment data with live-scan verification data,improvements in matches between live-scan and latent print dataare still needed. Data indicates that fully integrated palm printand fingerprint multi-biometric systems are widely used foridentification and verification of criminal subjects as well as insecurity access applications. But there are still significantchallenges in balancing accuracy with system cost. Imagematching accuracy may be improved by building and using largerdatabases and by employing more processing power, but thenpurchase and maintenance costs will most certainly rise as thesystems become larger and more sophisticated. Future challengesrequire balancing the need for more processing power with moreimprovements in algorithm technology to produce systems thatare affordable to all levels of law enforcement.Document References4Joe Bonino, Advisory Policy Board Joint Working Group Meeting.24 April 20021Peter Komarinski, “Automated Fingerprint IdentificationSystems”: 29.“NEC Solutions America Customer Honored By California’s Centerfor Digital Government,” NEC Press Release, December 16, 2004<http://www.necus.com/companies/20/NECSAMCustomerAwardByCalifCenterDigitalGovt.pdf#search='first%20automated%20palm%20system>.3“Cogent Systems has just received a contract to provide anAdvanced Integrated Cogent Automated Palm and FingerprintIdentification System (CAPFIS) for the States of Connecticut andRhode Island,” Cogent Systems Press Release<http://cogt.client.shareholder.com/ReleaseDetail.cfm?ReleaseID=145765>.452CrimTrak, “Fingerprints,” Commonwealth of Australia, 2005.Joe Bonino, Advisory Policy Board Joint Working Group Meeting.24 April 20026Shaila K. Dewan, “Elementary, Watson: Scan a Palm, Find aClue,” The New York Times, 21 November 2003.This Document Last Updated: 7 August 2006Page 7 of 10

Palm Print RecognitionAbout the National Science and Technology CouncilThe National Science and Technology Council (NSTC) wasestablished by Executive Order on November 23, 1993. ThisCabinet-level Council is the principal means within the executivebranch to coordinate science and technology policy across thediverse entities that make up the Federal research anddevelopment enterprise. Chaired by the President, themembership of the NSTC is made up of the Vice President, theDirector of the Office of Science and Technology Policy, CabinetSecretaries and Agency Heads with significant science andtechnology responsibilities, and other White House officials.A primary objective of the NSTC is the establishment of clearnational goals for Federal science and technology investments in abroad array of areas spanning virtually all the mission areas of theexecutive branch. The Council prepares research anddevelopment strategies that are coordinated across Federalagencies to form investment packages aimed at accomplishingmultiple national goals. The work of the NSTC is organized underfour primary committees; Science, Technology, Environment andNatural Resources and Homeland and National Security. Each ofthese committees oversees a number of sub-committees andinteragency working groups focused on different aspects ofscience and technology and working to coordinate the variousagencies across the federal government. Additional information isavailable atwww.ostp.gov/nstc.About the Subcommittee on BiometricsThe NSTC Subcommittee on Biometrics serves as part of theinternal deliberative process of the NSTC. Reporting to anddirected by the Committee on Homeland & National Security andthe Committee on Technology, the Subcommittee:Develops and implements multi-agency investmentstrategies that advance biometric sciences to meetpublic and private needs;Coordinates biometrics-related activities that are ofinteragency importance;Facilitates the inclusions of privacy-protectingprinciples in biometric system design;This Document Last Updated: 7 August 2006Page 8 of 10

Palm Print RecognitionMr. Brad Wing (DHS US-VISIT)Mr. David Young (FAA)Mr. Jim Zok (DOT)Special AcknowledgementsThe Communications ICP Team wishes to thank the followingexternal contributors for their assistance in developing thisdocument:B. Scott Swann, FBI/CJIS, for performing backgroundresearch and writing the first draftEd German, Stephen Meagher, Ron Smith, and theStandards ICP Team for reviewing the document andproviding numerous helpful commentsDocument SourceThis document, and others developed by the NSTC Subcommitteeon Biometrics, can be found atwww.biometrics.org.This Document Last Updated: 7 August 2006Page 10 of 10

You're reading the first 10 out of 10 pages of this docs, please download or login to readmore.